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Fusion network for face-based age estimation
conference contribution
posted on 2018-01-01, 00:00 authored by H Wang, X Wei, V Sanchez, Chang-Tsun LiChang-Tsun LiConvolutional Neural Networks (CNN) have been applied to age-related research as the core framework. Although faces are composed of numerous facial attributes, most works with CNNs still consider a face as a typical object and do not pay enough attention to facial regions that carry age-specific feature for this particular task. In this paper, we propose a novel CNN architecture called Fusion Network (Fusion-Net) to tackle the age estimation problem. Apart from the whole face image, the FusionNet successively takes several age-specific facial patches as part of the input to emphasize the age-specific features. Through experiments, we show that the FusionNet significantly outperforms other state-of-the-art models on the MORPH II benchmark.
History
Event
IEEE Signal Processing Society. Conference (25th : 2018 : Athens, Greece)Series
IEEE Signal Processing Society ConferencePagination
2675 - 2679Publisher
Institute of Electrical and Electronics EngineersLocation
Athens, GreecePlace of publication
Piscataway, N.J.Publisher DOI
Start date
2018-10-07End date
2018-10-10ISSN
1522-4880ISBN-13
9781479970612Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2018, IEEEEditor/Contributor(s)
[Unknown]Title of proceedings
ICIP 2018 : Proceedings of the 2018 25th IEEE International Conference on Image ProcessingUsage metrics
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